Methods for resolving lipoproteins with mass spectrometry

ABSTRACT

The present disclosure relates to methods of identifying components present in intact lipoprotein particles. Methods provided include single particle mass spectrometry, such as charge detection mass spectrometry (CDMS). Distinct subtypes and subpopulations that exist within lipoprotein density classes are determined based on simultaneously measured m/z and charge of ionized lipoprotein particles.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No. 16/647,955, filed Mar. 17, 2020, which is a national stage entry of International Patent Application No. PCT/US2018/051944, filed Sep. 20, 2018, which claims the benefit of and priority to U.S. Provisional Patent Application No. 62/561,184 filed Sep. 20, 2017, the disclosures of which are expressly incorporated herein by reference in their entireties.

STATEMENT OF GOVERNMENT RIGHTS

This invention was made with government support under CHE1531823 awarded by National Science Foundation. The government has certain rights in the invention.

BACKGROUND

Lipoproteins are involved in cholesterol transport in human plasma, have a diverse range of metabolic function, and serve as biomarkers for coronary artery disease. Lipoproteins are separated into classes based on the density of protein relative to the lipid composition, including high-density (HDL), low-density (LDL), and very low-density (VLDL). HDL is commonly referred to as the “good cholesterol,” while high amounts of LDL, or “bad cholesterol” have been implicated in coronary artery disease. There is an inverse correlation of HDL particle concentration and cardiovascular disease. (Castelli, W. P., et al. Circulation. 1977 (55) 767-772, incorporated by reference herein).

Each density class can be split into several subtypes which differ in size, composition, and metabolic properties. Furthermore, each subtype contains particles that differ in number of structural proteins, giving rise to many possible protein/lipid combinations that encompass a range of unique structures. The major density classes are linked through a series of lipid and protein exchange and conversion during metabolism, causing great variation in particle mass for a single population. Information about the many subtypes and diverse subpopulations of HDL is currently incomplete (Karathanasis, S. K., et al. Clin. Chem. 2017 (63) 196-210, incorporated by reference herein).

Characterizing macromolecular complexes is challenging because the resolution of conventional mass analyzers is not sufficient to assign charge states in the mass-to-charge (m/z) spectrum for heterogeneous and highly charged complexes, such as lipoproteins. Peaks in the m/z spectrum broaden and shift due to mass heterogeneity, either intrinsic or due to complex formation. Poorly resolved peaks in the m/z spectrum prevent charge state assignment and mass determination. Even sub-megadalton (MDa) sized complexes can contain hundreds of charges, making it a challenge to accurately determine mass.

While the development of new therapies for improved cardiovascular health would benefit from the development of techniques to measure HDL and LDL subtypes directly, particle diversity and heterogeneity impede characterization by analytical techniques known in the art. Thus, there is a need for new methods for analyzing lipoproteins.

SUMMARY

The present disclosure provides methods for resolving lipoproteins using single particle mass spectrometry, such as charge detection mass spectrometry (CDMS). Distinct subpopulations that exist within lipoprotein classes are revealed by correlating m/z and mass (or by other correlations involving mass, charge and m/z measurements).

According to one aspect of the present disclosure, a method of identifying components present in a lipoprotein includes subjecting the lipoprotein to mass spectrometry to produce ions, measuring a charge of each ion, measuring a mass-to-charge ratio of the ion, and identifying the components based on the mass of the lipoprotein.

In some embodiments, the charge of the ion and the mass-to-charge ratio of the ion may be measured simultaneously. In some embodiments, the charge of the ion and the mass-to-charge ratio of the ion may be measured using charge detection mass spectrometry. In some embodiments, the charge detection mass spectrometry may include focusing the ion into a linear ion trap, the linear ion trap comprising a charge detection cylinder. In some embodiments, the charge detection mass spectrometry may include focusing the ion into a linear ion trap and the linear ion trap incorporates a charge detection cylinder. In some embodiments, the linear ion trap may be a cone trap.

In some embodiments, the mass-to-charge ratio of the ion may be measured based on a time period that the ion takes to traverse the charge detection cylinder or the fundamental frequency at which the ion oscillates in the charge detection cylinder.

In some embodiments, the charge of the ion may be measured based on the amplitude of a signal due to the ion oscillating in the charge detection cylinder. In some embodiments, the ion may be trapped in the linear ion trap for a trapping period to determine the mass to charge ratio of the ion with sufficient accuracy. For example, the ion may be trapped in the linear ion trap for a trapping period of about 50 ms to about 150 MS.

In some embodiments, the lipoprotein may include one or more of high-density lipoprotein particles (HDL), low-density lipoprotein particles (LDL), and very low density lipoprotein particles (VLDL). In some embodiments, the method may further include estimating the diameter of a particle of the lipoprotein based on the mass of the ion and the density of a known lipoprotein subtype particle. In some embodiments, the lipoprotein may include a plasma lipoprotein, and the ion may be in the presence of one or more other lipoprotein particles.

In some embodiments, the mass of the ion may be within about 1 MDa of one or more other lipoprotein particles having a different subtype compared to the ion. In other embodiments, the mass of the ion may be within about 100 kDa of one or more other lipoprotein particles having a different subtype compared to the ion. Yet, in some embodiments, the mass of the ion may be within about 20 kDa of one or more other lipoprotein particles having a different subtype compared to the ion. In some embodiments, the ion may be an intact lipoprotein particle. In some embodiments, subjecting the lipoprotein to mass spectrometry to produce ions may include subjecting the lipoprotein without isolating a lipoprotein particle prior to subjecting the lipoprotein to mass spectrometry to produce an ion.

In some embodiments, the mass of the ion may be from about 100 kDa to about 80 MDa. In some embodiments, the mass of the ion may be from about 10 MDa to about 80 MDa. In some embodiments, the mass of the ion may be from about 100 kDa to about 3 MDa. In some embodiments, the method may include subjecting a single sample to a mass spectrometer.

According to another aspect of the present disclosure, a method for evaluating a patient's risk of cardiovascular disease includes identifying components present in a lipoprotein according to any of the preceding clauses. In some embodiments, identifying components present in a lipoprotein may include identifying components present in a lipoprotein in a blood sample.

According to another aspect of the present disclosure, a method of identifying components present in a lipoprotein includes correlating m/z and charge, or quantities derived therefrom, to determine quantities of HDL, LDL, and VLDL, wherein the lipoprotein is part of a sample comprising serum.

According to another aspect of the present disclosure, a method of identifying components present in a lipoprotein includes correlating m/z and charge, or quantities derived therefrom, to determine subtypes of HDL, LDL, and VLDL, wherein the lipoprotein is part of a sample comprising whole blood.

According to another aspect of the present disclosure, a method of identifying components of a lipoprotein present in a sample includes subjecting the sample to mass spectrometry to produce ions, measuring a charge of each ion, measuring a mass-to-charge ratio of the ion, and identifying the components based on the mass of the sample.

In some embodiments, the sample may include at least one of whole blood, plasma, or serum. In some embodiments, the charge of the ion and the mass-to-charge ratio of the ion may be measured simultaneously. In some embodiments, the charge of the ion and the mass-to-charge ratio of the ion may be measured using charge detection mass spectrometry. In some embodiments, the charge detection mass spectrometry may include focusing the ion into a linear ion trap, the linear ion trap comprising a charge detection cylinder. In some embodiments, the charge detection mass spectrometry may include focusing the ion into a linear ion trap and the linear ion trap incorporates a charge detection cylinder. In some embodiments, the linear ion trap may be a cone trap. In some embodiments, the mass-to-charge ratio of the ion may be measured based on a time period that the ion takes to traverse the charge detection cylinder or the fundamental frequency at which the ion oscillates in the charge detection cylinder.

In some embodiments, the charge of the ion may be measured based on the amplitude of a signal due to the ion oscillating in the charge detection cylinder. In some embodiments, the ion may be trapped in the linear ion trap for a trapping period to determine the mass to charge ratio of the ion with sufficient accuracy. In some embodiments, the ion may be trapped in the linear ion trap for a trapping period of about 50 ms to about 150 ms. In some embodiments, the lipoprotein may include one or more of high-density lipoprotein particles (HDL), low-density lipoprotein particles (LDL), and very low density lipoprotein particles (VLDL).

According to another aspect of the present disclosure, a method of identifying components present in a lipoprotein including subjecting the sample to mass spectrometry to produce ions, separating the ions based on a mass-to-charge ratio, selecting a subset of the ions based on the mass-to-charge ratio, dissociating the selected ions into fragments, and analyzing the fragments to identify the components present in the lipoprotein.

In some embodiments, selecting the subset of the ions based on the mass-to-charge ratio may include selecting a subset of the ions that correspond to a subpopulation of the lipoprotein based on the mass-to-charge ratio. For example, the mass-to-charge ratio may correspond to a subpopulation of the lipoprotein.

In some embodiments, selecting the subset of the ions based on the mass-to-charge ratio may include selecting a subset of the ions using a mass spectrometer. For example, the mass spectrometer may be a time-of-flight mass spectrometer, a quadrupole mass spectrometer, a linear and non-linear ion trap mass spectrometer, a Fourier transform mass spectrometer, a magnetic sector mass spectrometer, an Orbitrap mass spectrometer, or a double focusing mass spectrometer.

In some embodiments, dissociating the selected ions into the fragments may include dissociating the selected ions using a dissociation method. For example, the dissociation method may be collision induced dissociation, collisionally activated dissociation, surface induced dissociation, photo-induced dissociation, electron-impact induced dissociation, electron transfer dissociation, and/or electron capture dissociation. The photo-induced dissociation may further include infrared multiple photon dissociation and/or UV photodissociaton.

In some embodiments, analyzing the fragments to identify the components present in the lipoprotein may include analyzing the fragments using mass spectrometry and/or charge detection mass spectrometry. In some embodiments, the lipoprotein comprises one or more of high-density lipoprotein particles (HDL), low-density lipoprotein particles (LDL), and very low density lipoprotein particles (VLDL).

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1A is a mass spectrum for HDL overlaid with a scatter plot of m/z versus mass where each point represents a single ion;

FIG. 1B is a mass spectrum for HDL-2 overlaid with a scatter plot of m/z versus mass where each point represents a single ion;

FIG. 1C is a mass spectrum for HDL-3 overlaid with a scatter plot of m/z versus mass where each point represents a single ion;

FIG. 2 is a mass spectrum for LDL overlaid with a scatter plot of m/z versus mass where each point represents a single ion;

FIG. 3 is a schematic diagram of a charge detection mass spectrometry (CDMS) apparatus used in connection with the present methods;

FIG. 4A is a mass spectrum measured for HDL overlaid with a scatter plot of m/z versus mass where each point represents a single ion. HDL subclasses are resolved in the scatterplot;

FIG. 4B illustrates a mass distribution for HDL identical to that shown in FIG. 4A along with mass distributions for the HDL subpopulations identified in the scatterplot of m/z versus mass in FIG. 4A;

FIG. 4C illustrates mass distributions for the HDL subpopulations overlaid with scales giving approximate masses for HDL particles with n_(I) copies of Apolipoprotein A-I and n_(II) copies of Apolipoprotein A-II, wherein the large digits represent the number of Apo A-I and the small digits represent the number of Apo A-II; and

FIG. 5 illustrates a mass spectrum measured for LDL overlaid with a scatter plot of m/z versus mass where each point represents a single ion. Subpopulations of LDL are resolved in the scatterplot. Note that these subpopulations have overlapping mass distributions.

DETAILED DESCRIPTION

The present invention will now be described with reference to the accompanying drawings, in which representative embodiments of the invention are shown. This invention may, however, be embodied in different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.

Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. All publications, patent applications, patents, and other references mentioned herein are incorporated by reference herein in their entirety.

The present disclosure provides methods for resolving lipoproteins by measuring the mass-to-charge ratio (m/z) and charge (z) of lipoprotein ions passing through a mass spectrometer. In some embodiments, these methods are used to characterize high-density (HDL) and low-density (LDL) lipoprotein particles, even when the particles are highly heterogeneous.

It is to be understood that lipoproteins may comprise micellar molecular structures having several structural proteins and lipid molecules. Lipoproteins may comprise tens of hundreds of lipid molecules.

HDL is comprised of approximately 50% protein by mass, of which, two major structural proteins apolipoprotein AI (Apo-AI) and apolipoprotein AII (Apo-AII), contribute to about 70% and about 20% of the total protein content, respectively. The additional 10% can be attributed to enzymes and lipid transfer proteins, as well as >5% corresponding to minor proteins. Lipid transfer proteins are mainly responsible for the exchange of lipids between lipoprotein particles, and thus, contribute to the unfixed masses of HDL particles. The primary contributor to heterogeneity of HDL is the conformational flexibility of the main structural protein Apo-AI. It dictates particle structure through scavenging phospholipids and thus driving the formation of small, medium, and large particles. As particle size increases, the number of Apo-AI proteins also increases; some HDL subtypes carry more than 4 Apo-AI molecules per particle. In addition, Apo-AI has the capacity to bind and interact with additional proteins where specific protein-protein complexes have been observed to form with HDL particles. Over 50 accessory proteins and more than 200 individual lipid species have been identified in human HDL structure and transport. Without having a fixed stoichiometry, combined with the dynamic nature of exchangeable proteins, it may be difficult to parse out a fixed mass for each subtype. In some embodiments, a range of masses and sizes may be used to broadly characterize the observed subpopulations within HDL and its subtypes.

The high density subtypes HDL-2 and HDL-3 can be separated further into five distinct subpopulations HDL2b, HDL2a, HDL3a, HDL3b, and HDL3c. Each subpopulation differs in size and protein composition, with the main differences between HDL-2 and HDL-3 subtypes corresponding to their lipid rich and lipid-poor construction, respectively.

Low density lipoproteins are greater in size than high density particles; the diameter of LDL is at least twice as large as HDL and incorporates hundreds more lipid molecules. The low density lipoprotein classes suffer from inherent heterogeneity due to the high ratio of lipids and cholesterol relative to protein. Larger VLDL is converted to LDL in the bloodstream through a series of delipidation steps. Structural protein apolipoprotein-B100 (apoB-100) is non-exchangeable and does not vary in terms of number of molecules per particle. Instead, there are several other ancillary proteins that comprise LDL that are dynamic and can be exchanged during cholesterol transport.

The methods of the present disclosure can be employed to establish the mass and stoichiometry of lipoprotein particles. In some embodiments, the methods described herein can be employed to distinguish between various lipoprotein particle subtypes. Subpopulations and subtypes that exist within lipoprotein classes may be identified by correlating m/z, charge, and mass to reveal distinct subpopulations that exist within lipoprotein classes and subtypes that would be difficult or impossible to observe by ensemble techniques alone. In some embodiments, the present methods are used to observe low abundant subpopulations that exist within subtypes of HDL. The methods of this disclosure can also be used to resolve differences in lipoprotein structure, morphology, orientation, size, chemical status, and the like. The lipoprotein particles used in connection with the present disclosure may comprise intact lipoprotein particles. Additionally, the lipoprotein particles may be analyzed without the use of isolation or without the use of extensive isolation.

It is to be understood that the masses of the lipoprotein particles used in connection with the present methods may range from about 100 kilodaltons (kDa) to about 10 megadaltons (MDa), about 100 kilodaltons (kDa) to about 5 megadaltons (MDa), about 100 kilodaltons (kDa) to about 3 megadaltons (MDa), or about 100 kilodaltons (kDa) to about 2 megadaltons (MDa), or about 10 megadalton (MDa) to about 80 megadaltons (MDa).

In some embodiments, many lipoprotein classes are present in a sample used in connection with the methods described herein. In some embodiments, the methods comprise subjecting a single sample to a mass spectrometer. In some embodiments, samples containing isolated subgroups are measured as standards to aid in characterizing particle properties such as stoichiometry.

Analytical methods described herein include single particle mass spectrometry, such as charge detection mass spectrometry (CDMS), which is a single particle technique that measures the mass-to-charge ratio (m/z) and charge (z) for each individual ion. Single particle mass spectrometry may allow for differentiating heterogeneous species in the mass spectrum by measuring, such as simultaneously measuring, m/z and z and directly deducing mass therefrom. Multiplying m/z and z gives the mass of a particle directly. In addition, the measured mass and known density information can be used to estimate the particle diameter. This information may be used for characterizing lipoprotein subtypes and subgroups that vary slightly in size and protein composition.

For example, single particle mass spectrometry methods described herein are capable of resolving HDL subtypes and subgroups within heterogeneous HDL samples by correlating the mass and m/z measurements (or by other correlations involving mass, charge and m/z measurements). The single particle measurement afforded by single particle mass spectrometry allows for low abundance populations to be observed. The ability to measure single particles one at a time allows for the measurement of low abundance species within the mixture of particles. Single particle mass spectrometry is also capable of providing the accurate mass of intact lipoprotein particles.

Nonlimiting examples of single particle mass spectrometry approaches that can be employed in the methods of this disclosure include time of flight mass spectrometry with a cryogenic detector, charge detection mass spectrometry (CDMS), quadrupole ion trap mass spectrometry with optical detection and charge detection, Fourier transform ion cyclotron resonance, Orbitrap mass spectrometry and micromechanical/nanomechanical oscillators. A detailed description of various single molecule mass spectrometry approaches included in this disclosure can be found in Keifer & Jarrold (“Single molecule mass spectrometry” Mass Spectrometry Reviews; DOI 10.1002/mas.21495 (2016) Wiley Periodicals, Inc.; the entire contents of which are incorporated by reference herein). In some embodiments, information on lipoprotein subtypes is obtained by correlating m/z and mass (or by other correlations involving mass, charge and m/z measurements). This information may be obtained from the m/z spectrum alone if the results are calibrated by single particle mass spectrometry, such as CDMS. In such embodiments, a conventional mass spectrometer may be used to obtain information on subtypes once standards are calibrated, such as by CDMS.

In some embodiments, the methods described herein are used alongside additional techniques used to detect, quantify, and/or characterize lipoprotein composition. Additional techniques may comprise one or more of liquid chromatography, nuclear magnetic resonance, size exclusion chromatography, electrofiltration or two-dimensional electrophoretic mobility, and related proteomics approaches.

Charge detection mass spectrometry (CDMS) is a single particle technique, where the m/z and z of individual ions are measured concurrently, thereby allowing direct determination of the mass of each ion. Examples of CDMS are described in Keifer et al. (Anal. Chem., 2015, 87 (20), pp 10330-10337) and Pierson et al. (J. Am. Soc. Mass Spectrom. (2015) 26:1213-1220), which are incorporated by reference herein. The methods described herein include using CDMS to analyze heterogeneous mixtures that are intractable by conventional MS methods.

Exemplary CDMS systems are described in Contino, N. C., et al., Int. J. Mass Spectrom. 2013, 345-347, 153-159; Contino, N. C.; et al., J. Am. Soc. Mass Spectrom. 2013, 24, 101-108; Pierson, E. E.; et al., Int. J. Mass Spectrom. 2013, 337, 50-56; Pierson, E. E.; et al., J. Am. Soc. Mass Spectrom. 2015, 26, 1213-1220; Keifer, D. Z.; et al., Anal. Chem. 2015, 87, 10330-10337, incorporated by reference herein. In some embodiments, CDMS comprises passing ions through a conductive cylinder. The charge induced by the ion when it is in the cylinder is detected by a charge sensitive preamplifier. The time the ion takes to traverse the length of the conductive tube is related to the m/z, while the amplitude of the induced charge imparted onto the cylinder can be used to determine z. In some embodiments, the detection cylinder is placed inside an ion trap so that an ion oscillates back and forth through the detection cylinder many times, improving the signal to noise ratio.

Referring to FIG. 3 , one embodiment of a CDMS apparatus for carrying out the methods of the present disclosure is shown. The lipoprotein standards are ionized via a commercial nanoelectrospray ionization source before entering the charge detection mass spectrometer. Ions enter the instrument through a heated capillary and pass through an RF hexapole, an RF quadrupole, and an ion lens. Ions are energy selected within a dual hemispherical deflection energy analyzer and then focused into a linear ion trap, such as a cone trap, that contains the charge detection cylinder. To initiate a trapping event, a potential is placed on the rear end cap so that ions are reflected back through the trap. After a short delay, a potential is placed on the front end cap to close the trap and cause the ion to oscillate back and forth through the charge detection cylinder. The ion oscillating back and forth through the detection cylinder induces a periodic signal which is amplified, digitized, and then analyzed by a Fortran program using fast Fourier transforms. The m/z is derived from the fundamental frequency and the charge (z) is derived from the magnitude of the fundamental and first harmonic.

In some embodiments, a trapping period in the linear ion trap may be greater than about 10 ms, about 25 ms, about 50 ms, about 75 ms, about 100 ms, about 150 ms, about 200 ms, about 300 ms, about 400 ms, about 3 s, or about 30 s. Additionally, the trapping time may be from about 10 ms to about 1000 ms, about 25 ms to about 1000 ms, about 50 ms to about 1000 ms, about 75 ms to about 1000 ms, about 100 ms to about 1000 ms, about 150 ms to about 1000 ms, about 200 ms to about 1000 ms, or about 300 ms to about 1000 ms.

In some embodiments of the present disclosure, the single particle mass spectrometry can be carried out or performed by time of flight mass spectrometry, charge detection mass spectrometry, quadrupole ion trap mass spectrometry, Fourier transform ion cyclotron resonance and/or Orbitrap mass spectrometry. In some embodiments the single particle mass spectrometry can be carried out or performed with micromechanical/nanomechanical oscillator. These approaches for carrying out single particle mass spectrometry can be employed individually or in any combination.

In some embodiments, single particle mass spectrometry can be carried out or performed on a commercial mass spectrometer retro-fitted for single particle measurements. As one nonlimiting example, a single particle detector can be retrofitted to an existing instrument (e.g., a commercial instrument) that would allow single particle mass measurements to be performed. In one nonlimiting example, the commercial instrument could be a quadrupole time of flight (QTOF) mass spectrometer.

Sample preparation for carrying out the methods of this disclosure may be carried out according to protocols described herein as well as protocols known in the art for conventional mass spectrometry and single particle mass spectrometry methods. Such methods can involve transferring a sample to a solution containing a volatile salt.

In some embodiments, volatile, structure preserving buffers are utilized. In some embodiments, the salt can be ammonium acetate, although other salts may be used in some embodiments. Ammonium acetate may be present in a concentration of about 1 mM to about 15 mM, about 5 mM to about 15 mM, about 10 mM to about 15 mM, about 1 mM to about 12.5 mM, about 5 mM to about 12.5 mM, about 10 mM to about 12.5 mM, about 5 mM, about 10 mM, or about 12.5 mM. In some embodiments, the buffer has a pH of about 7 to about 8 or about 7.5.

In some embodiments, the methods of the present disclosure comprise analyzing lipoproteins obtained from a patient to evaluate the patient's risk for cardiovascular disease. The methods may comprise taking total measures of HDL and LDL to evaluate a patient's risk for cardiovascular disease. The HDL may comprise several subtypes with several subgroups that populate each subtype. Similarly, LDL may comprise of several subtypes. In some embodiments, the methods described herein comprise directly measuring subtypes and/or subgroups within a lipoprotein mixture. Such methods may be utilized to improve risk assessment through characterization and/or identification of particular subgroups.

In some embodiments, tandem mass spectrometry or mass spectrometry/mass spectrometry (MS/MS) techniques may be used to analyze lipoprotein subpopulations. For example, ions with a narrow band of m/z values may be selected using a mass spectrometer, and the ions may be broken into fragments using a variety of methods, such as, collision induced dissociation, collisionally activated dissociation, surface induced dissociation, photo-induced dissociation (including infrared multiple photon dissociation and UV photodissociaton), electron-impact induced dissociation, electron transfer dissociation, and electron capture dissociation. The mass spectrometer may be a time-of-flight mass spectrometer, a quadrupole mass spectrometer, a linear and non-linear ion trap mass spectrometer, a Fourier transform mass spectrometer, a magnetic sector mass spectrometer, a Orbitrap mass spectrometer, a double focusing mass spectrometer, or any other type of mass spectrometer used for conventional mass spectrometry (MS). As discussed further below, CDMS measurements have shown that the lipoprotein populations and subpopulations have a narrow range of m/z values. This allows a specific subpopulation of lipoprotein to be selected using the mass spectrometer and dissociated into fragments that can be analyzed by conventional MS, CDMS, or a combination of both conventional MS and CDMS to identify the components present in the selected lipoprotein subpopulation.

In some embodiments, CDMS may be used in connection with the present methods to analyze a broad range of masses encompassing many lipoprotein classes in a single experiment. For example, CDMS may be employed to characterize lipoproteins directly from plasma without the need for extensive isolation or enhancing the purity of the plasma. It should be appreciated that, in some embodiments, CDMS may be used to analyze whole blood, plasma, or serum to determine abundances of lipoprotein populations (e.g., high-density (HDL), low-density (LDL), and very low-density (VLDL)) and subpopulations. Although whole blood, plasma, and serum are complex mixtures of many different components with widely varying concentrations, lipoprotein populations and subpopulations may be isolated from other components (e.g., proteins) present in the whole blood, plasma, and serum by correlating the charge, mass, and mass-to-charge (m/z) values measured by CDMS. As discussed further below, CDMS measurements have shown that the lipoprotein populations and subpopulations have a range of m/z values.

Definitions

The singular forms “a,” “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise.

Furthermore, the term “about,” as used herein when referring to a measurable value such as an amount of the length of a polynucleotide or polypeptide sequence, dose, time, temperature, and the like, is meant to encompass variations of ±20%, ±10%, ±5%, ±1%, ±0.5%, or even ±0.1% of the specified amount.

Also as used herein, “and/or” refers to and encompasses any and all possible combinations of one or more of the associated listed items, as well as the lack of combinations when interpreted in the alternative (“or”).

Unless the context indicates otherwise, it is specifically intended that the various features of the invention described herein can be used in any combination.

Moreover, the present invention also contemplates that in some embodiments of the invention, any feature or combination of features set forth herein can be excluded or omitted.

As used herein, the terms “reduce,” “reduces,” “reduction” and similar terms mean a decrease of at least about 25%, 35%, 50%, 75%, 80%, 85%, 90%, 95%, 97% or more. As used herein, the terms “enhance,” “enhances,” “enhancement” and similar terms indicate an increase of at least about 5%, 10%, 20%, 25%, 50%, 75%, 100%, 150%, 200%, 300%, 400%, 500% or more.

Likewise, an “isolated” lipoprotein means a lipoprotein that is at least partially separated from at least some of the other components of the naturally occurring organism. In representative embodiments an “isolated” lipoprotein is enriched by at least about 10-fold, 100-fold, 1000-fold, 10,000-fold or more as compared with the starting material.

As used herein, by “isolate: or “purify” (or grammatical equivalents) a lipoprotein, it is meant that the lipoprotein is at least partially separated from at least some of the other components in the starting material. In representative embodiments an “isolated” or “purified” lipoprotein is enriched by at least about 10-fold, 100-fold, 1000-fold, 10,000-fold or more as compared with the starting material.

Having described the present invention, the same will be explained in greater detail in the following examples, which are included herein for illustration purposes only, and which are not intended to be limiting to the invention.

EXAMPLES Materials

Low density lipoprotein (LDL), high density lipoprotein (HDL), and HDL subtypes HDL-2 an HDL-3 were purchased from Academy Bio-Medical Company (Houston, Tex., USA). The high density lipoprotein standards were buffer exchanged into 5, 10, or 12.5 mM ammonium acetate (NH₄OAc) at pH 7.5 via micro Bio-Spin® columns (Bio-Rad Laboratories, Hercules, Calif., USA). Low density lipoprotein was dialyzed overnight into 12.5 NH₄OAc at pH 7.5. The final concentration of the lipoprotein standards after exchange into NH₄OAc was <1 mg/mL.

The lipoprotein standards were purified via ultracentrifugation and isolated from a range of densities. The HDL standard contained all species within a density range of 1.063-1.210 g/mL The subtypes of HDL, HDL-2 and HDL-3, were isolated from a smaller band of densities of 1.063 to 1.120 g/mL and 1.120 to 1.210 g/mL, respectively. Instrumentation

The lipoprotein standards were ionized via a commercial nanoelectrospray ionization source before entering a home-built charge detection mass spectrometer described in Contino, N. C., et al., Int. J. Mass Spectrom. 2013, 345-347, 153-159; Contino, N. C.; et al., J. Am. Soc. Mass Spectrom. 2013, 24, 101-108; Pierson, E. E.; et al., Int. J. Mass Spectrom. 2013, 337, 50-56; Pierson, E. E.; et al., J. Am. Soc. Mass Spectrom. 2015, 26, 1213-1220; Keifer, D. Z.; et al., Anal. Chem. 2015, 87, 10330-10337, incorporated by reference herein. Ions entered the instrument through a heated capillary and were transported through an ion funnel, RF hexapole and RF quadrupole. A DC offset on the hexapole set the nominal ion energy around 100 eV/charge. The ions extracted from the quadrupole were focused into the entrance of the dual hemispherical deflection energy analyzer (HDA). The energy selected ions were then focused into a modified cone trap that contained the charge detection cylinder. To initiate a trapping event, a potential was placed on the rear end cap so that ions were reflected back through the trap. After a short delay, a potential was placed on the front end cap to close the trap and caused the ion to oscillate back and forth through the charge detection cylinder. A trapping period of 100 ms was employed, after which the trap was opened (both end caps set to ground) and the trapping cycle repeated. The ion oscillating back and forth through the detection cylinder induced a periodic signal which was amplified, digitized, and then analyzed by a Fortran program using fast Fourier transforms. The m/z was derived from the fundamental frequency and the charge (z) was derived from the magnitude of the fundamental and first harmonic.

Results

FIGS. 1A-1C show the mass spectra recorded for HDL, subtype HDL-2, and subtype HDL-3, respectively. Overlaid on each mass spectrum is a scatter plot of m/z (right hand axis) versus mass where each point represents a single ion. In CDMS, the m/z and mass of individual ions can be directly correlated. Clusters of points represent ions that share similar m/z values which correspond to particular populations within same subtype that have slightly different stoichiometry.

The mass spectrum for isolated HDL is shown in FIG. 1A. The most prominent peak in the mass spectrum was centered at 229 kDa and showed a high mass tail that extended up to 1 MDa. Ions were detected out to 3 MDa, albeit in low abundance. Without intending to be bound by theory, the CDMS peak shape was expected to be Gaussian with a width determined by the uncertainties in the m/z and charge measurements. For a homogenous population of only a single species, the expected peak width for the main feature in the mass spectrum would be 17.8 kDa. Instead, the full width at half maximum measured 138 kDa, indicating the peak was made up of contributions from many species. The overlaid scatter plot (right hand axis) showed at least four densely populated clusters at well-defined m/z values of 6.60, 7.50, 8.90, and 10.7 kTh. The center masses for each subpopulation were determined by isolating the ions in each cluster, binning the masses into a histogram, and then fitting the histogram with a Gaussian. Although the ions are well separated by m/z, the four clusters of ions differed only slightly in mass, corresponding to masses of 165, 200, 250 and 376 kDa, respectively.

FIG. 1B illustrates the mass spectrum for subtype HDL-2. The most abundant feature in the mass spectrum was a peak centered at 238 kDa. A high mass shoulder is present starting around 0.5 MDa and extended toward 1 MDa in mass. A low abundant continuum of ions was observed out to 3 MDa. Noise did not contribute to the low abundant ion counts observed at masses above 1 MDA as empty, partial, and multiple ion trapping events were discarded during data analysis. All ion intensity reported in the mass spectrum were from real ions that had been trapped for the entire duration of the 100 ms trapping event. The overlaid scatter plot displaying the relationship of m/z versus mass for each ion showed evidence of at least six distinct subpopulations with m/z below 20 kTh. Three densely populated clusters at m/z 6.6, 7.5, and 8.8 kTh contributed to the most abundant feature in the mass spectrum and correspond to masses of 161, 197, and 239 kDa, respectively. Two additional clusters at 10.1 and 13.4 kTh appeared to contribute to the high mass shoulder with the center of masses at 326 and 550 kDa, respectively.

FIG. 1C illustrates the mass spectrum for the smallest of the high density lipoprotein subtypes, HDL-3. There were two distinct features observed in the mass spectrum: a high intensity peak centered at 170 kDa and a smaller and a lower abundant feature centered at 340 kDa. The ion counts diminished as masses reached 2 MDa. Very few ions were present above 2 MDa. Eight distinct clusters were observed in the overlaid scatter plot. The four clusters that contained the majority of the total ion intensity were in the low m/z regime positioned at 5.8, 6.8, 7.7, and 9.5 kTh. These clusters correspond to populations with masses of 138, 175, 213, and 342 kDa, respectively. The additional high m/z clusters at 11.5, 15.0, and 25.0 kTh correspond to high mass particles centered around 0.5, 0.9, and 1.1 MDa and were responsible for the broad but low-abundant distribution of masses that followed the 340 kDa peak in the mass spectrum.

Each subtype, HDL-2 and HDL-3, overlapped in density with the HDL sample, therefore, it is expected that similar subpopulations were observed among the three standards. Specifically, HDL and HDL-2 shared two clusters of ions centered around m/z values of 6.5 and 7.5 kTh corresponding to particles having masses of 165 and 200 kDa, respectively. Without intending to be bound by theory, although the exact stoichiometry is unknown, it is likely that these two clusters were of the same subpopulation in both isolated samples.

The subpopulations with masses of 175, 212, and 342 kDa in FIG. 1C agree with values estimated from literature and are tentatively assigned to subpopulations of HDL-3a, HDL-3b, and HDL-3c, respectively. The masses observed for HDL and HDL-2 subpopulations in FIGS. 1A and 1B do not directly conform to particles of known stoichiometry. Currently, more than 10 HDL subspecies have been identified and are classified by pre-beta and pre-alpha type particles. Without intending to be bound by theory, it is possible that an assortment of small, medium, and large HDL particles as well as pre-beta and pre-alpha subspecies were observed by CDMS.

The LDL mass spectrum in FIG. 2 showed a high abundant peak at approximately 200 kDa followed by a broad distribution of ions centered around 2.14 MDa. The overlaid scatter plot showed that the ions contributing to the 200 kDa peak spanned a range of 5 to 10 kTh with no discernible clusters, as were observed in the HDL standards. The ions with masses centered at 2.14 MDa showed a more disperse distribution of ions with m/z values ranging from 18 to 38 kTh and having a mean value of 27 kTh. Without intending to be bound by theory, it is likely the highly disperse range of masses and m/z values for LDL were due to differing amounts of lipid and cholesterol cargo. There is evidence for small, high density LDL where presence is expected to be a biomarker for coronary artery disease. Ions with masses 0.5 to 2 MDa are tentatively assigned to the more dense subspecies of LDL.

In addition, a high intensity peak was observed in the LDL standard near 200 kDa. Because the structural protein of LDL apolipoprotein B-100 weighs in at approximately 550 kDa, the intense low mass peak is attributed to contamination from HDL that may have occurred during the isolation process.

With the direct measurement of mass and known density, the particle diameters of each subtype and subpopulations were estimated. The particle diameters were in good agreement with those particle diameters in literature, reporting diameters of 7-12, 9.2-10.2, 7.5-8.8 and 21-27 nm for HDL, HDL-2, HDL-3, and LDL, respectively. Although some of the species observed in HDL-2 had diameters below 7 nm, those particles can be attributed to overlap from HDL particles in the isolation process.

FIG. 4A illustrates a CDMS spectrum measured for an HDL sample where seven subpopulations have been identified in the scatter plot of m/z versus mass. In FIG. 4B, the mass distributions of the subpopulations identified in FIG. 4A are plotted along with the overall mass distribution of this HDL sample. The mass distributions for the subpopulations can be accounted for by HDL particles with different numbers of the key structural proteins Apolipoprotein A-1 (Apo A-I) and Apolipoprotein A-II (Apo A-II) as described by Lutomski, Gordon, Remaley, and Jarrold (“Resolution of Lipoprotein Subclasses by Charge Detection Mass Spectrometry”, Anal. Chem. 2018, 90, 6353-6356. DOI: 10.1021/acs.analchem.8b01127; the entire contents of which are incorporated by reference herein).

As discussed above, given that HDL is around 50% protein and that the two major structural proteins Apo A-I (28,081 Da) and Apo A-II (17,252 Da) together contribute around 90% of the total protein, a particle with n_(I) Apo A-I proteins and n_(II) Apo A-II proteins would be expected to have a mass (in kDa) of around

m(n _(I) ,n _(II))=(28.081×n _(I)+17.252×n _(II))/0.45   (1)

Masses predicted by Equation 1 are shown by the scales in FIG. 4C. The large digits give the number of Apo A-I proteins, with n_(I) ranging from 1 to 6. The smaller digits give the number of Apo A-II proteins, with n_(II) ranging from zero to n_(II)≤n_(I). The points on the scales give the masses from Equation 1 for specific combinations of n_(I) and n_(II). For example, for n_(I)=1 and n_(II)=2, the expected mass from Equation 1 is 163 kDa. A distribution of masses is expected for each n_(I),n_(II) combination, and the masses given by Equation 1 are only approximate. However, they provide a starting point for assigning the subpopulations resolved in FIGS. 4A and 4B. For n_(I)=2, there are points on the scale in FIG. 4C at 125, 163, and 201 kDa corresponding to n_(II)=0, 1, and 2. These match up with the three lowest mass components in FIGS. 4B and 4C (which have average masses of 129/126, 165/163, and 200/208 kDa). The resolving power degrades as the mass increases so peaks due to different n_(II) are not expected to be resolved for higher masses. The resolved component centered on around 250/261 kDa in FIGS. 4B and 4C can be attributed to n_(I)=3 and n_(II)=1-2. Similarly, the peak at 321/327 kDa can be attributed to n_(I)=4 and n_(II)=1-3. Particles with n_(I)=5 and 6 may contribute to the high mass tail on the 321-327 kDa peak and to the 511/463 kDa peak. The highest mass component in FIG. 4 at 756 kDa is large for an HDL particle. A proteomics study of the HDL sample revealed the presence of Apo B100, the main structural protein of LDL. Thus, an LDL impurity may be responsible for some of the high mass component observed in the HDL spectrum.

FIG. 5 illustrates a mass spectrum measured for LDL which shows the resolution of subclasses in the scatter plot of an LDL sample. In contrast to HDL, where the subclasses have partly discrete mass distributions, the subclasses of LDL have broad and overlapping mass distributions. 

What is claimed:
 1. A method of measuring lipoprotein particles of at least one subtype of a density class of intact lipoprotein particles present in a sample containing the density class of intact lipoprotein particles, the method comprising: a) producing lipoprotein ions from the density class of intact lipoprotein particles contained in the sample, b) simultaneously measuring a charge and a mass-to-charge ratio of each of the lipoprotein ions, c) determining a mass of each of the lipoprotein ions based on the measured charge and mass-to-charge ratio values thereof, d) identifying the at least one subtype of the density class of intact lipoprotein particles based on the determined masses and measured charges of the lipoprotein ions, and e) determining diameters of lipoprotein particles of the identified at least one subtype based on the determined masses and known densities of the lipoprotein particles of the identified at least one subtype.
 2. The method of claim 1, wherein the sample contains a plurality of density classes of intact lipoprotein particles, and wherein producing the lipoprotein ions comprises producing the lipoprotein ions from each of the plurality of density classes of intact lipoprotein particles, and wherein identifying the at least one subtype comprises identifying the at least one subtype of one of the plurality of density classes of intact lipoprotein particles based on the determined masses and measured charges of the lipoprotein ions.
 3. The method of claim 2, wherein the sample comprises whole blood, plasma or serum.
 4. The method of claim 2, further comprising: (f) identifying at least one subtype of another one of the plurality of density classes of intact lipoprotein particles based on the determined masses and measured charges of the lipoprotein ions, and (g) determining diameters of lipoprotein particles of the identified at least one subtype of the another one of the plurality of density classes of intact lipoprotein particles based on the determined masses and known densities of the lipoprotein particles of the identified at least one subtype of the another one of the plurality of density classes of intact lipoprotein particles.
 5. The method of claim 1, wherein the charge and the mass-to-charge ratio of each of the lipoprotein ions are measured simultaneously using charge detection mass spectrometry.
 6. The method of claim 5, wherein the charge detection mass spectrometry comprises, for each of the lipoprotein ions, focusing the lipoprotein ion into a linear ion trap.
 7. The method of claim 6, wherein the linear ion trap includes a charge detection cylinder, and wherein the lipoprotein ion oscillates back and forth in the linear ion trap each time passing through the charge detection cylinder, and wherein the charge of the lipoprotein ion is measured by measuring a charge induced by the lipoprotein ion on the charge detection cylinder each of multiples times the lipoprotein ion passes through the charge detection cylinder, and wherein the mass-to-charge ratio of the lipoprotein ion is measured based on a time period spent by the lipoprotein ion each of the multiple times the lipoprotein ion passes through the charge detection cylinder or a fundamental frequency of oscillation of the lipoprotein ion back and forth through the charge detection cylinder.
 8. A method of measuring lipoprotein particles in at least one subpopulation of a subtype of a density class of intact lipoprotein particles present in a sample containing the density class, or the subtype of the density class, of intact lipoprotein particles, the method comprising: a) producing lipoprotein ions from the density class, or the subtype of the density class, of intact lipoprotein particles contained in the sample, b) simultaneously measuring a charge and a mass-to-charge ratio of each of the lipoprotein ions, c) determining a mass of each of the lipoprotein ions based on the measured charge and mass-to-charge ratio values thereof, d) identifying the at least one subpopulation of the subtype of the density class of intact lipoprotein particles based on the determined masses and measured charges of the lipoprotein ions, and e) determining diameters of lipoprotein particles in the identified at least one subpopulation based on the determined masses and known densities of the lipoprotein particles in the identified at least one subpopulation.
 9. The method of claim 8, wherein the sample contains a plurality of density classes of intact lipoprotein particles, and wherein producing the lipoprotein ions comprises producing the lipoprotein ions from each of the plurality of density classes of intact lipoprotein particles, and wherein identifying the at least one subpopulation of the subtype of the density class of intact lipoproteins comprises identifying the at least one subpopulation of the subtype of one of the plurality of density classes of intact lipoprotein particles based on the determined masses and measured charges of the lipoprotein ions.
 10. The method of claim 9, wherein the sample comprises whole blood, plasma or serum.
 11. The method of claim 9, further comprising: (f) identifying at least one subpopulation of the subtype of another one of the plurality of density classes of intact lipoprotein particles based on the determined masses and measured charges of the lipoprotein ions, and (g) determining diameters of lipoprotein particles in the identified at least one subpopulation of the subtype of the another one of the plurality of density classes of intact lipoprotein particles based on the determined masses and known densities of the lipoprotein particles of the identified at least one subpopulation of the subtype of the another one of the plurality of density classes of intact lipoprotein particles.
 12. The method of claim 8, wherein the charge and the mass-to-charge ratio of each of the lipoprotein ions are measured simultaneously using charge detection mass spectrometry.
 13. The method of claim 12, wherein the charge detection mass spectrometry comprises, for each of the lipoprotein ions, focusing the lipoprotein ion into a linear ion trap.
 14. The method of claim 13, wherein the linear ion trap includes a charge detection cylinder, and wherein the lipoprotein ion oscillates back and forth in the linear ion trap each time passing through the charge detection cylinder, and wherein the charge of the lipoprotein ion is measured based on a charge induced by the lipoprotein ion on the charge detection cylinder each of multiple times the lipoprotein ion passes through the charge detection cylinder, and wherein the mass-to-charge ratio of the lipoprotein ion is measured based on a time period spent by the lipoprotein ion each of the multiple times the lipoprotein ion passes through the charge detection cylinder or a fundamental frequency of oscillation of the lipoprotein ion back and forth through the charge detection cylinder.
 15. A method of identifying components of lipoprotein particles in a density class, subtype of the density class or subpopulation of the subtype of the density class of intact lipoprotein particles present in a sample containing the intact lipoprotein particles, the method comprising: a) producing lipoprotein ions from the intact lipoprotein particles contained in the sample, b) measuring mass-to-charge ratios of the lipoprotein ions, c) selecting a subset of the measured lipoprotein ions having mass-to-charge ratios within a selected range of mass-to-charge ratios, d) dissociating the lipoprotein ions in the selected subset into fragment ions, and e) simultaneously measuring a charge and a mass-to-charge ratio of the fragment ions; f) determining masses of the fragment ions based on the measured charge and mass-to-charge ratio values thereof; and g) identifying the components of the lipoprotein particles in the density class, subtype of the density class or subpopulation of the subtype of the density class of intact lipoprotein particles based on the determined masses of the fragment ions.
 16. The method of claim 15, wherein selecting the subset of the measured lipoprotein ions comprises selecting, based on the measured mass-to-charge ratios of the lipoprotein ions, a subset of the measured lipoprotein ions that corresponds to the subtype of the density class of the intact lipoprotein particles.
 17. The method of claim 15, wherein selecting the subset of the measured lipoprotein ions comprises selecting, based on the measured mass-to-charge ratios of the lipoprotein ions, a subset of the measured lipoprotein ions that corresponds to the subpopulation of the subtype of the density class of the intact lipoprotein particles.
 18. The method of claim 15, wherein the sample comprises whole blood, plasma or serum.
 19. The method of claim 15, wherein the charge and the mass-to-charge ratio of each of the fragment ions are measured simultaneously using charge detection mass spectrometry, and wherein the charge detection mass spectrometry comprises, for each of the fragment ions, focusing the fragment ion into a linear ion trap.
 20. The method of claim 19, wherein the linear ion trap includes a charge detection cylinder, and wherein the fragment ion oscillates back and forth in the linear ion trap each time passing through the charge detection cylinder, and wherein the charge of the fragment ion is measured based on a charge induced by the fragment ion on the charge detection cylinder each of multiple times the fragment ion passes through the charge detection cylinder, and wherein the mass-to-charge ratio of the fragment ion is measured based on a time period spent by the fragment ion each of the multiple times the fragment ion passes through the charge detection cylinder or a fundamental frequency of oscillation of the fragment ion back and forth through the charge detection cylinder. 